In the development of the Semantic Web researchers and industry experts agree that scalability can only be obtained by reducing standard reasoning tasks to query evaluation over (deductive) databases. From a theoretical viewpoint much has been done. Conversely, from a practical point of view, only a few reasoning services have been developed, which however typically can only deal with lightweight ontologies. To fill the gap, the paper presents owl2dlv, a modern Datalog system for evaluating SPARQL queries over very large OWL 2 knowledge bases. owl2dlv builds on the well-known ASP system dlv by incorporating novel optimizations sensibly reducing memory consumption and a server-like behavior to support multiple-query scenarios. The high potential of owl2dlv is outlined by the results of an experiment on data-intensive benchmarks, and confirmed by the interest of a major international industrial player, which has stimulated and partially supported the work.

Querying large expressive horn ontologies

Alviano M.;Calimeri F.;Costabile R.;Cuteri B.;Fiorentino A.;Fusca D.;Germano S.;Laboccetta G.;Leone N.;Manna M.;Perri S.;Reale K.;Ricca F.;Veltri P.;Zangari J.
2019-01-01

Abstract

In the development of the Semantic Web researchers and industry experts agree that scalability can only be obtained by reducing standard reasoning tasks to query evaluation over (deductive) databases. From a theoretical viewpoint much has been done. Conversely, from a practical point of view, only a few reasoning services have been developed, which however typically can only deal with lightweight ontologies. To fill the gap, the paper presents owl2dlv, a modern Datalog system for evaluating SPARQL queries over very large OWL 2 knowledge bases. owl2dlv builds on the well-known ASP system dlv by incorporating novel optimizations sensibly reducing memory consumption and a server-like behavior to support multiple-query scenarios. The high potential of owl2dlv is outlined by the results of an experiment on data-intensive benchmarks, and confirmed by the interest of a major international industrial player, which has stimulated and partially supported the work.
2019
Datalog; DLV; Ontology-based query answering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/297994
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